{"id":"W1544223034","doi":"10.1007/3-540-47922-8_2","title":"AERO: An Outsourced Approach to Exception Handling in Multi-agent Systems","year":2002,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Multi-Agent Systems and Negotiation","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Sketch; Exception handling; Host (biology); Outsourcing; Work (physics); Multi-agent system; Computer security; Service (business); Distributed computing; Artificial intelligence; Operating system; Business; Engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002873173,0.0008248726,0.001327304,0.0005795109,0.001047951,0.003547771,0.003661422,0.0009982759,0.008043195],"category_scores_gemma":[0.004374517,0.001126498,0.001111072,0.0009432908,0.001485974,0.004581691,0.004315291,0.00282909,0.001540773],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006817225,"about_ca_system_score_gemma":0.001760786,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002425941,"about_ca_topic_score_gemma":0.003062593,"domain_scores_codex":[0.9976748,0.000530666,0.000179329,0.0002392439,0.001117097,0.0002588158],"domain_scores_gemma":[0.9969974,0.0006940767,0.000193193,0.001568285,0.0003350686,0.000211987],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001075511,0.0003645642,0.001481858,0.0007027994,0.0002241813,0.0008182845,0.001579247,0.09542431,0.01741222,0.2149193,0.03346502,0.6325328],"study_design_scores_gemma":[0.0003333557,0.0002278141,0.00103233,0.0001353573,0.0001729268,0.0005666008,0.0002858644,0.7020351,0.02331609,0.150444,0.1213316,0.0001189721],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.006348591,0.0002379708,0.9800462,0.0002102058,0.0001483525,0.0001289643,0.000104945,0.006966352,0.00580853],"genre_scores_gemma":[0.1904335,0.0007411912,0.7837803,0.0004089124,0.0002355582,0.0003061497,0.0006702163,0.003073419,0.0203507],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008043195,"threshold_uncertainty_score":0.02690721,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06323396977989709,"score_gpt":0.2663961588240794,"score_spread":0.2031621890441823,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}